from load_dataset import *
from plots import *
ld = LoadDataset()
ld.add_well("../E.csv",54.216024,23.317928)
ld.add_well("../F.csv",54.245660,23.334958)
k,m = ld.add_well("../L.csv",54.223237,23.351474)
m
p = LogsPlots(k)
p.plot_a_log(1)
p.plot_a_log(2)
p.plot_property('RHOB')
hl = ld.height_adjustment()
from grid import *
g1 = grid(k,50)
p = g1.grid_main()
from dataframe import *
n_dd = merge_dataset(hl).merge(['RHOB'])
n_dd.head()
from sklearn_ import *
model = interpolation(n_dd)
model.validation(SVR)
from dataframe import *
populate = populate(p)
test_df = populate.populated_dataframe(hl)
test_df = model.prediciton(test_df,algorithm=SVR)
test_df.head()
rp = result_plots()
rp.plot_3d(test_df,'RHOB')